A Fusion Model-Based Label Embedding and Self-Interaction Attention for Text Classification

A Fusion Model-Based Label Embedding and Self-Interaction Attention for Text Classification

Text classification is a pivotal task in NLP (Natural Language Processing), which has received widespread attention recently. Most of the existing methods leverage the power of deep learning to improve the performance of models. However, these models ignore the interaction information between all th...

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Bibliographic Details
Main Authors: Yanru Dong, Peiyu Liu, Zhenfang Zhu, Qicai Wang, Qiuyue Zhang
Format: Article
Language:English
Published: IEEE 2020-01-01
Series:IEEE Access
Subjects:
Text classification
text representations
label embedding
Online Access:https://ieeexplore.ieee.org/document/8908707/

Internet

https://ieeexplore.ieee.org/document/8908707/

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